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Hong-Lin Xu,Guang-Hong Chen,Yu-Ting Wu,Ling-Peng Xie,Zhang-Bin Tan,Bin Liu,Hui-Jie Fan,Hong-Mei Chen,Gui-Qiong Huang,Min Liu,Ying-Chun Zhou 고려인삼학회 2022 Journal of Ginseng Research Vol.46 No.1
Background: Panax ginseng Meyer (P. ginseng), a herb distributed in Korea, China and Japan, exerts benefits on diverse inflammatory conditions. However, the underlying mechanism and active ingredients remains largely unclear. Herein, we aimed to explore the active ingredients of P. ginseng against inflammation and elucidate underlying mechanisms. Methods: Inflammation model was constructed by lipopolysaccharide (LPS) in C57BL/6 mice and RAW264.7 macrophages. Molecular docking, molecular dynamics, surface plasmon resonance imaging (SPRi) and immunofluorescence were utilized to predict active component. Results: P. ginseng significantly inhibited LPS-induced lung injury and the expression of proinflammatory factors, including TNF-a, IL-6 and IL-1b. Additionally, P. ginseng blocked fluorescence-labeled LPS (LPS488) binding to the membranes of RAW264.7 macrophages, the phosphorylation of nuclear factor-kB (NF-kB) and mitogen-activated protein kinases (MAPKs). Furthermore, molecular docking demonstrated that ginsenoside Ro (GRo) docked into the LPS binding site of toll like receptor 4 (TLR4)/myeloid differentiation factor 2 (MD2) complex. Molecular dynamic simulations showed that the MD2-GRo binding conformation was stable. SPRi demonstrated an excellent interaction between TLR4/MD2 complex and GRo (KD value of 1.16 × 10<SUP>-9</SUP> M). GRo significantly inhibited LPS488 binding to cell membranes. Further studies showed that GRo markedly suppressed LPS-triggered lung injury, the transcription and secretion levels of TNF-α, IL-6 and IL-1β. Moreover, the phosphorylation of NF-kB and MAPKs as well as the p65 subunit nuclear translocation were inhibited by GRo dose-dependently. Conclusion: Our results suggest that GRo exerts anti-inflammation actions by direct inhibition of TLR4 signaling pathway.
온라인을 통한 호텔 선택요소가 구매의도에 미치는 구조적 관계연구
계림림 ( Gui Lin Lin ),신홍철 ( Shin Hong Cheol ) 한국호텔리조트학회(구 한국호텔리조트카지노산학학회) 2021 호텔리조트연구 Vol.20 No.3
Accommodation is an important part of tourism, and the hotel online booking market is also attractive. Compared to existing offline reservations by travelers, purchase reservations are increasing at the Hotel Website or Online Travel Agency (OTA). The purpose of this study is to study the relationship between hotel online purchasing intentions by selecting factors such as quality, price, facility, location, service, room, etc. based on hotel options online. The data analysis is conducted based on 326 respondents who have been used hotel online reservations. To summarize the analysis results of this study, first, facilities, location, and room dimensions were found to have a statistically significant effect on quality factors. Second, facilities, location, service, and room dimensions were found to have a statistically significant effect on price factors. Third, it was confirmed that quality, price, and service dimensions had a statistically significant effect on hotel purchase intention. This study is meaningful in that the results obtained from empirical research provided a framework for establishing practical strategies by encouraging website users to use and specifying important choices that can be used continuously.
Deep BBN Learning for Health Assessment toward Decision-Making on Structures under Uncertainties
Hong Pan,Guoqing Gui,Zhibin Lin,Changhui Yan 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.3
Structural systems are often exposed to harsh environment, while these environmental factors in turn could degrade the system over time. Their health state and structural conditions are key for structural safety control and decision-making management. Although great efforts have been paid on this field, the high level of variability due to noise and other interferences, and the uncertainties associated with data collection, structural performance and in-service operational environments post great challenges in finding information to assist decision making. The machine learning techniques in recent years have been gaining increasing attentions due to their merits capturing information from statistical representation of events and thus enabling making decision. In this study, the deep Bayesian Belief Network Learning (DBBN) was used to extract structural information and probabilistically determine structural conditions. Different to conventional shallow learning that highly relies on the quality of the hand-crafted features, the deep learning is an end-to-end method to encode the information and interpret vast amount of data with minimizing or no features. A case study was conducted to address the methods for structure under viabilities and uncertainties due to operation, damage and noise interferences. Numerical results revealed that the deep learning exhibits considerably enhanced accuracy for structural diagnostics, as compared to the supervised shallow learning. With predetermined training set, the DBBN could accurately determine the structural health state in terms of damage level, which could dramatically help decision making for further structural retrofit or not. Note that the noise interference could contaminate the data representation and in turn increase the difficulty of the data mining, though the deep learning could reduce the impacts, as compared to conventional shallow learning techniques.
Carboxymethyl Flavonoids and A Monoterpene Glucoside from Selaginella moellendorffii
Hong-Sheng Wang,Ling Sun,Yue-Hu Wang,Ya-Na Shi,Gui-Hua Tang,Fu-Wei Zhao,Hong-Mei Niu,Chun-Lin Long,Ling Li 대한약학회 2011 Archives of Pharmacal Research Vol.34 No.8
A new dihydroflavone, 5-carboxymethyl-7,4'-dihydroxyflavonone (1), and its glucoside 5-carboxymethyl-7,4'-dihydroxyflavonone-7-O-β-D-glucopyranoside (2), and one new monoterpene glucoside, (4Z,6E)-2,7-dimethyl-8-hydroxyocta-4,6-dienoic acid 8-O-β-D-glucopyranoside (3), were isolated from the whole plants of Selaginella moellendorffii. Their structures were determined by spectroscopic methods and chemical transformation. Compound 2 was evaluated for the ability to enhance glucose consumption in normal and insulin-resistant L6 muscle cells induced by high concentrations of insulin and glucose. Glucose consumption in insulin-resistant cells (but not in normal cells) was increased 15.2 ± 3.3% (p < 0.01) by compound 2 at a concentration of 0.1 μM in the presence of insulin (1 nM).
Guoqing Gui,Hong Pan,Zhibin Lin,Yonghua Li,Zhijun Yuan 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.2
Rapid detecting damages/defeats in the large-scale civil engineering structures, assessing their conditions and timely decision making are crucial to ensure their health and ultimately enhance the level of public safety. Advanced sensor network techniques recently allow collecting large amounts of data for structural health monitoring and damage detection, while how to effectively interpret these complex sensor data to technical information posts many challenges. This paper presents three optimization-algorithm based support vector machines for damage detection. The optimization algorithms, including grid-search, partial swarm optimization and genetic algorithm, are used to optimize the penalty parameters and Gaussian kernel function parameters. Two types of feature extraction methods in terms of time-series data are selected to capture effective damage characteristics. A benchmark experimental data with the 17 different scenarios in the literature were used for verifying the proposed data-driven methods. Numerical results revealed that all three optimized machine learning methods exhibited significantly improvement in sensitivity, accuracy and effectiveness over conventional methods. The genetic algorithm based SVM had a better prediction than other methods. Two different feature methods used in this study also demonstrated the appropriate features are crucial to improve the sensitivity in detecting damage and assessing structural health conditions. The findings of this study are expected to help engineers to process big data and effectively detect the damage/defects, and thus enable them to make timely decision for supporting civil infrastructure management practices.
Cheng Wang,Gang-Lin Yan,Shao-Wu Lü,Chun-Hong Sui,Yang Zhao,Ya-Wei Xu,Gang Zhao,Jun-jie Xu,Ping-Sheng Gong,Gui-Min Luo,Ying Mu 한국생물공학회 2013 Biotechnology and Bioprocess Engineering Vol.18 No.1
Glutathione peroxidase (GPX) is one of the important members of the antioxidant enzyme family. It can catalyze the reduction of hydroperoxides with glutathione to protect cells against oxidative damage. Single-chain variable fragment (scFv) can be converted into seleniumcontaining single-chain variable fragment (Se-scFv) by chemical modification of the hydroxyl groups in scFv, thus Se-scFv possesses GPX activity and becomes a prodrug. To improve the expression of scFv and simplify its purification steps, Single-protein production (SPP) system was used to express scFv and chemical modification was used to synthesize Se-scFv. Therefore, we must construct a new scFv-WCD1-lessACA gene, which can express its mRNA not containing any ACA sequences and express its amino acid sequence of target protein (scFv) being same to scFv-WCD1. In this way, the scFv-WCD1-lessACA can be only expressed in SPP system and no other background proteins in the cells could be expressed. The expression results showed that high level of scFv-WCD1-lessACA synthesis was at least sustained for 96 h in the virtual absence of background protein synthesis. Then, selenocysteine (Sec) was incorporated into the scFv-WCD1-lessACA by chemical modification and resulted in Se-scFv-WCD1-lessACA. The enzymatic characteristics of Se-scFv-WCD1-lessACA were determined. GPX activity was 2,563 U/μmol,its binding constant for GSH was 0.687 ×105/mol. Moreover,Se-scFv-WCD1-lessACA was confirmed to have a strong antioxidant ability to protect mitochondria against oxidative damage induced by Vc/Fe2+ (mitochondrial damage model),suggesting that Se-scFv-WCD1-lessACA has potential application for protection of mitochondrial damage induced by reactive oxygen species (ROS).
Upregulation of MicroRNA 181c Expression in Gastric Cancer Tissues and Plasma
Cui, Mei-Hua,Hou, Xiao-Lin,Lei, Xiao-Yan,Mu, Fang-Hong,Yang, Gui-Bin,Yue, Lin,Fu, Yi,Yi, Guo-Xing Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.5
Objective: To test the microRNA-181c (miR-181c) expression in tissues and plasma of gastric cancer (GC) cases, analyze any correlations, and explore the possibility of miR-181c as a potential molecular marker for GC diagnosis. Materials and Methods: Relative miR-181c expression levels in cancers and plasma from 30 GC patients was tested using reverse transcription-real-time fluorescent quantitation PCR and compared to that in samples from 30 gastric ulcer and 30 chronic gastritis patients. Results: The miR-181c expression level in the GC tissues was significantly higher than that in the gastric ulcer and chronic gastritis tissues (P = 0.000), as was the miR-181c expression level in the GC plasma (P = 0.000). We determined that miR-181c expression in GC plasma was positively correlated to its expression in the GC tissues (P = 0.000). Conclusions: The expression of miR-181c is upregulated in GC tissues and plasma, and the miR-181c expression level in GC plasma is positively correlated to that in the corresponding cancer tissues. Plasma miR-181c is possibly a new serological marker for GC diagnosis.
Wen Zhong-Ling,Yang Min-Kai,Fazal Aliya,Liao Yong-Hui,Cheng Lin-Run,Hua Xiao-Mei,Hu Dong-Qing,Shi Ji-Sen,Yang Rong-Wu,Lu Gui-Hua,Qi Jin-Liang,Zhi Hong,Qian Qiu-Ping,Yang Yong-Hua 한국미생물·생명공학회 2020 Journal of microbiology and biotechnology Vol.30 No.8
In this study, two soybean genotypes, i.e., aluminum-tolerant Baxi 10 (BX10) and aluminumsensitive Bendi 2 (BD2), were used as plant materials and acidic red soil was used as growth medium. The soil layers from the inside to the outside of the root are: rhizospheric soil after washing (WRH), rhizospheric soil after brushing (BRH) and rhizospheric soil at two sides (SRH), respectively. The rhizosphere bacterial communities were analyzed by high-throughput sequencing of V4 hypervariable regions of 16S rRNA gene amplicons via Illumina MiSeq. The results of alpha diversity analysis showed that the BRH and SRH of BX10 were significantly lower in community richness than that of BD2, while the WRH exhibited no significant difference between BX10 and BD2. Among the three sampling compartments of the same soybean genotype, WRH had the lowest community richness and diversity while showing the highest coverage. Beta diversity analysis results displayed no significant difference for any compartment between the two genotypes, or among the three different sampling compartments for any same soybean genotype. However, the relative abundance of major bacterial taxa, specifically nitrogen-fixing and/or aluminum-tolerant bacteria, was significantly different in the compartments of the BRH and/or SRH at phylum and genus levels, indicating genotype-dependent variations in rhizosphere bacterial communities. Strikingly, as compared with BRH and SRH, the WRH within the same genotype (BX10 or BD2) always had an enrichment effect on rhizosphere bacteria associated with nitrogen fixation